Tag Archives: PENS

Motivation & Engagement in Gameplay


At the peak of my academic career, there are numerous theories and frameworks that I interface with on a near-daily basis. From PENS, to MDA/MMDA, to Flow and intensity/engagement curves, I am surrounded by proposed solutions for the various shortcomings of game design theory.

Now, to attempt to combine all of this research into a single, unified practical framework would be completely foolhardy. So here I go:

What You Need to Know

There are a few things that are essential to know before going any deeper. I will quickly outline the frameworks and theories I reference below:

PENSThe Player Experience of Need Satisfaction is a heavily-researched framework that theorizes that sustained player engagement (retention) can be measured by a game’s ability to deliver on three central axes: autonomy, competence, and relatedness.

MDAThe Mechanics/Dynamics/Aesthetics framework explores the relationship between the components of a game (mechanics) and the end-user experience (aesthetics).

MMDA – Developed by Benjamin Ellinger (DigiPen), the Multimedia/Dynamics/Aesthetics framework is a more thorough, detailed breakdown and extension of the MDA framework.

Flow – A psychological state of focus and immersion first proposed by Mihály Csíkszentmihályi, flow takes place in a mental channel between anxiety and boredom.

Intensity/Engagement Curve – The theory that the most resonant experiences have an intensity/engagement arc that corresponds to the standard structure of the 3-act story arc.

Aesthetics and Motivators

MDA/MMDA focuses on building a library of often-interconnected gameplay aesthetics (high-level gameplay experiences, such as “challenge” or “discovery”). These aesthetics can be broken down into their dynamic and mechanical constituents, but this process can become fairly nebulous when transitioning between each lens. To help improve our ability as designers to achieve sustainable gameplay from a desired aesthetic, let’s try combining MDA/MMDA with PENS:


Here we’ve taken each of the standard MDA/MMDA aesthetics, and derived a rough distribution of the PENS axes to represent how they achieve sustained engagement. Each distribution is fairly unique and can direct a game towards the desired aesthetic if each axis is properly represented.

But there is still room to go deeper from here using both flow theory (to explain growth) and engagement/intensity curves to explain exact execution.

Reinforcing Engagement Pillars

The next step in being able to use these theoretical frameworks in a unified, practical process is dissecting how to deliver on each of the three PENS axes. To do that, we’ll need to better define each PENS axis:

Autonomy – “The experience of volition or choice in one’s decisions and actions” (PENS, 11).  At its core, Autonomy is about freedom, and can manifest itself in a variety of forms, including personal expression and identity development.

Competence – “The intrinsic need to feel a sense of mastery or effectance in what one is doing” (PENS, 5). Competence is more about the sensation of excellence; the state of being greater than one once was, and that one’s time invested in the game has been appropriately rewarded.

Relatedness – “The intrinsic desire to connect with others in a way that feels authentic and supportive” (PENS, 13). Relatedness, at its essence, is about a feeling of purpose; that whatever one does and has done will impact others either directly (playing together in-game) or indirectly (discussing stories out-of-game).

Now what if we were to see each PENS axis as having its own flow channel for maximized performance and learning? It would probably look something like this:

PENS & Flow

Now we can look at each axis as having its own flow channel that must be maintained. This also inherently means that it is possible to be in flow state for one axis while being out of flow for another. This occurrence is not only possible, but is also expected, as players will be constantly transitioning between axes (and subsequently flow channels).

And that brings us to the final piece of the puzzle that will complete this unified framework.

Pacing Flow States

Intensity/Engagement curves have been used extensively in design theory to discuss gameplay pacing as it relates to the 3-act structure of storytelling. In theory, all contained gameplay experiences share the following attributes with the three-act structure:

Hook – A promise of what the central conflict will entail. The player spots an enemy soldier amidst an ongoing firefight.

Call to Action – The moment when the hero decides to get involved in the central conflict. The player raises the rifle and looks down the scope at the target.

Rising Action – Small, episodic conflicts that progress the central conflict. The player attempts to line up the reticle with the target. The target keeps moving, extending the conflict.

Crisis – Something crippling happens to the hero. The player takes the shot, and becomes vulnerable for a moment while the bullet travels (and the player begins to reload).

Climax – The central conflict is resolved despite the crisis. The enemy is slain.

Epilogue – The relevance of the central conflict’s resolution is exposed for closure. The player proceeds to take his fallen enemy’s weapon.

Even in the warfare example above, there is a rough adherence to the 3-act structure that leads to a stronger, more meaningful storytelling experience. And wherever you find strong meaning, you begin to encroach on a flow state. So for the last piece of the puzzle, let us combine flow theory and intensity/engagement curves:

Flow Curve

Instead of seeing intensity/engagement curves as a single-branch measurement, we are now looking at several concurrently developing curves – one curve for each PENS axis flow channel.

More essential than the idea of separate curves is the understanding that these curves are not (and should not be) identical; each curve will create different peaks and valleys as the game experience develops, and each PENS axis will typically be emphasized in an alternating fashion.

The exact structure of these curves is essential to the gameplay experience, but cannot be determined at the theoretical level without limiting the creative possibility space of the designers.


There are a number of theories and frameworks traversing the world of game design theory, but little progress is being made to help unify these frameworks. By locating crossover territory between MDA/MMDA, PENS, Flow Theory, and Intensity/Engagement Curves, we’re able to see a new theoretical network:

  • Rough ideas beget MDA/MMDA aesthetics
  • Each MDA/MMDA Aesthetic begets a PENS axis distribution
  • Each PENS axis is developed through Flow, the mental state of optimal experience
  • And each Flow channel is built through an Intensity/Engagement curve

Given the fractal nature of intensity/engagement curves, this progression then continues recursively until the mechanical workspace of the designer is too minute to effectively adjust. And while the exact execution of the intensity/engagement curve are still left up to the creative minds of designers, we can begin to construct a more consistent, procedural way to create sustained engagement from even the simplest game ideas.


* Updates *

10/23/13 – Updated the Relatedness flow chart to read “Overdependence” instead of “Insignificance”. This better illustrates the anxiety involved with having too many social obligations (too many people are dependent on you).

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